• Title/Summary/Keyword: research data

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Analyzing the Main Paths and Intellectual Structure of the Data Literacy Research Domain (데이터 리터러시 연구 분야의 주경로와 지적구조 분석)

  • Jae Yun Lee
    • Journal of the Korean Society for information Management
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    • v.40 no.4
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    • pp.403-428
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    • 2023
  • This study investigates the development path and intellectual structure of data literacy research, aiming to identify emerging topics in the field. A comprehensive search for data literacy-related articles on the Web of Science reveals that the field is primarily concentrated in Education & Educational Research and Information Science & Library Science, accounting for nearly 60% of the total. Citation network analysis, employing the PageRank algorithm, identifies key papers with high citation impact across various topics. To accurately trace the development path of data literacy research, an enhanced PageRank main path algorithm is developed, which overcomes the limitations of existing methods confined to the Education & Educational Research field. Keyword bibliographic coupling analysis is employed to unravel the intellectual structure of data literacy research. Utilizing the PNNC algorithm, the detailed structure and clusters of the derived keyword bibliographic coupling network are revealed, including two large clusters, one with two smaller clusters and the other with five smaller clusters. The growth index and mean publishing year of each keyword and cluster are measured to pinpoint emerging topics. The analysis highlights the emergence of critical data literacy for social justice in higher education amidst the ongoing pandemic and the rise of AI chatbots. The enhanced PageRank main path algorithm, developed in this study, demonstrates its effectiveness in identifying parallel research streams developing across different fields.

Utilization of EPRI ChemWorks tools for PWR shutdown chemistry evolution modeling

  • Jinsoo Choi;Cho-Rong Kim;Yong-Sang Cho;Hyuk-chul Kwon;Kyu-Min Song
    • Nuclear Engineering and Technology
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    • v.55 no.10
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    • pp.3543-3548
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    • 2023
  • Shutdown chemistry evolution is performed in nuclear power plants at each refueling outage (RFO) to establish safe conditions to open system and minimize inventory of corrosion products in the reactor coolant system (RCS). After hydrogen peroxide is added to RCS during shutdown chemistry evolution, corrosion products are released and are removed by filters and ion exchange resins in the chemical volume control system (CVCS). Shutdown chemistry evolution including RCS clean-up time to remove released corrosion products impacts the critical path schedule during RFOs. The estimation of clean-up time prior to RFO can provide more reliable actions for RCS clean-up operations and transients to operators during shutdown chemistry. Electric Power Research Institute (EPRI) shutdown calculator (SDC) enables to provide clean-up time by Co-58 peak activity through operational data from nuclear power plants (NPPs). In this study, we have investigated the results of EPRI SDC by shutdown chemistry data of Co-58 activity using NPP data from previous cycles and modeled the estimated clean-up time by EPRI SDC using average Co-58 activity of the NPP. We selected two RFO data from the NPP to evaluate EPRI SDC results using the purification time to reach to 1.3 mCi/cc of Co-58 after hydrogen peroxide addition. Comparing two RFO data, the similar purification time between actual and computed data by EPRI SDC, 0.92 and 1.74 h respectively, was observed with the deviation of 3.7-7.2%. As the modeling the estimated clean-up time, we calculated average Co-58 peak concentration for normal cycles after cycle 10 and applied two-sigma (2σ, 95.4%) for predicted Co-58 peak concentration as upper and lower values compared to the average data. For the verification of modeling, shutdown chemistry data for RFO 17 was used. Predicted RCS clean-up time with lower and upper values was between 21.05 and 27.58 h, and clean-up time for RFO 17 was 24.75 h, within the predicted time band. Therefore, our calculated modeling band was validated. This approach can be identified that the advantage of the modeling for clean-up time with SDC is that the primary prediction of shutdown chemistry plans can be performed more reliably during shutdown chemistry. This research can contribute to improving the efficiency and safety of shutdown chemistry evolution in nuclear power plants.

An Investigation on Characteristics and Intellectual Structure of Sociology by Analyzing Cited Data (사회학 분야의 연구데이터 특성과 지적구조 규명에 관한 연구)

  • Choi, Hyung Wook;Chung, EunKyung
    • Journal of the Korean Society for information Management
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    • v.34 no.3
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    • pp.109-124
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    • 2017
  • Through a wide variety of disciplines, practices on data access and re-use have been increased recently. In fact, there has been an emerging phenomenon that researchers tend to use the data sets produced by other researchers and give scholarly credit as citation. With respect to this practice, in 2012, Thomson Reuters launched Data Citation Index (DCI). With the DCI, citation to research data published by researchers are collected and analyzed in a similar way for citation to journal articles. The purpose of this study is to identify the characteristics and intellectual structure of sociology field based on research data, which is one of actively data-citing fields. To accomplish this purpose, two data sets were collected and analyzed. First, from DCI, a total of 8,365 data were collected in the field of sociology. Second, a total of 12,132 data were collected from Web of Science with a topic search with 'Sociology'. As a result of the co-word analysis of author provided-keywords for both data sets, the intellectual structure of research data-based sociology was composed of two areas and 15 clusters and that of article-based sociology was composed with three areas and 17 clusters. More importantly, medical science area was found to be actively studied in research data-based sociology and public health and psychology are identified to be central areas from data citation.

A Study on the Data Availability Statements of Researchers Affiliated with Korean Institutions: Focusing on the PLOS ONE (국내 기관 소속 연구자의 데이터 가용성 진술 (Data Availability Statements) 현황 연구: PLOS ONE 학술지를 중심으로)

  • Byoung-Goon An;Jeayeon Byun
    • Journal of the Korean Society for information Management
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    • v.40 no.1
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    • pp.225-258
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    • 2023
  • The purpose of this study is to investigate the current status and characteristics of research data sharing by domestic researchers by analyzing the data sharing mechanism and repository specified in DAS of papers authored by domestic researchers. To this end, in this study, papers of researchers belonging to domestic institutions published in PLOS ONE from 2014 to 2022 were selected as the subject of the study. First of all, the status of DAS's existence in the papers was identified, the types of data-sharing mechanisms were analyzed using precedent studies, and the trend of changes in each data-sharing mechanism over time was investigated. As a result, it was found that DAS was written in 99.6% of the target papers, and the types of data-sharing mechanisms were similar to international patterns, but preferred types were changing over time. Afterward, focusing on repositories among data sharing mechanisms, the number and ratio of repositories mentioned in DAS were identified, and the trend of changes in use of the five repositories mentioned a lot was analyzed in a time series. In addition, the presentation method, type, and validity of the data access point mentioned along with the repository were also investigated. It was confirmed that the top five frequently mentioned repositories account for 60% of all repository mentions, and the use of a repository dealing with data codes is increasing; in addition, it was found that most of the data access points presented with the repository were valid.

Nonlinear Canonical Correlation Analysis for Paralysis Disease Data

  • Shin, Yang-Kyu
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.3
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    • pp.515-521
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    • 2004
  • Categorical data are mostly found in oriental medical research. The nonlinear canonical correlation analysis does not assume an interval level of measurement. In this paper, we apply nonlinear canonical correlation analysis to quantification and explain how similar sets of variables are to one another for paralysis disease data.

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Effects of Product Recommendations on Customer Behavior in e-Commerce : An Empirical Analysis of Online Bookstore Clickstream Data (클릭스트림 데이터를 활용한 전자상거래에서 상품추천이 고객 행동에 미치는 영향 분석)

  • Lee, Hong-Joo
    • Journal of the Korean Operations Research and Management Science Society
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    • v.33 no.3
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    • pp.59-76
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    • 2008
  • Studies of recommender systems have focused on improving their performance in terms of error rates between the actual and predicted preference values. Also, many studies have been conducted to investigate the relationships between customer information processing and the characteristics of recommender systems via surveys and web-based experiments. However, the actual impact of recommendation on product pages for customer browsing behavior and decision-making in the commercial environment has not, to the best of our knowledge, been investigated with actual clickstream data. The principal objective of this research is to assess the effects of product recommendation on customer behavior in e-Commerce, using actual clickstream data. For this purpose, we utilized an online bookstore's clickstream data prior to and after the web site renovation of the store. We compared the recommendation effects on customer behavior with the data. From these comparisons, we determined that the relevant recommendations in product pages have positive relationships with the acquisition of customer attention and elaboration. Additionally, the placing of recommended items in shopping cart is positively related to suggesting the relevant recommendations. However, the frequencies at which the recommended items were purchased did not differ prior to and after the renovation of the site.

Design and Implementation of an Urban Safety Service System Using Realtime Weather and Atmosphere Data (실시간 기상 및 대기 데이터를 활용한 도시안전서비스 시스템 설계 및 구현)

  • Hwang, Hyunsuk;Seo, Youngwon;Jeon, Taegun;Kim, Changsoo
    • Journal of Korea Multimedia Society
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    • v.21 no.5
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    • pp.599-608
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    • 2018
  • As natural disasters are increasing due to the unusual weather and the modern society is getting complicated, the rapid change of the urban environment has increased human disasters. Thus, citizens are becoming more anxious about social safety. The importance of preparation for safety has been suggested by providing the disaster safety services such as regional safety index, life safety map, and disaster safety portal application. In this paper, we propose an application framework to predict the urban safety index based on user's location with realtime weather/atmosphere data after creating a predication model based on the machine learning using number of occurrence cases and weather/atmosphere history data. Also, we implement an application to provide traffic safety index with executing preprocessing occurrence cases of traffic and weather/atmosphere data. The existing regional safety index, which is displayed on the Si-gun-gu area, has been mainly utilized to establish safety plans for districts vulnerable to national policies on safety. The proposed system has an advantage to service useful information to citizens by providing urban safety index based on location of interests and current position with realtime related data.

Utilization of SketchUp for Efficient 3D Modeling of Buildings

  • Park, Joon Kyu;Lee, Keun Wang
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.35 no.5
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    • pp.431-438
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    • 2017
  • The information management system for urban planning, urban management and related decision making is increasing an importance in recent years. Especially, the information about 3D buildings in urban area is necessary for urban management related precise location based service. However, it takes a lot of time, effort, and costs to produce 3D modeling data of buildings. These problems have been found in many studies, but the research to solve these problems is still necessary. In this study, we have tested an efficient 3D modeling method of building to solve these problems. SketchUp was used to test 3D modeling methods with OSM(OpenStreetMap) data. The other 3D modeling method using a digital map was tested. The 3D modeling of building data was efficient using PlaceMaker, which can use OSM data. In addition, modeling was possible through simple editing of the digital map and automatic building generation. The efficiency of the research results is presented by comparing with the traditional method based on the regulation and the stadard man power issued by Korean government. These two 3D modeling methods of building tested through the study can be used as basic data for related research and work. Additional studies should be conducted to improve the accuracy of the building model and determine how to obtain height data efficiently.

A Bayesian Approach for the Analysis of Times to Multiple Events : An Application on Healthcare Data (다사건 시계열 자료 분석을 위한 베이지안 기반의 통계적 접근의 응용)

  • Seok, Junhee;Kang, Yeong Seon
    • Journal of the Korean Operations Research and Management Science Society
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    • v.39 no.4
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    • pp.51-69
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    • 2014
  • Times to multiple events (TMEs) are a major data type in large-scale business and medical data. Despite its importance, the analysis of TME data has not been well studied because of the analysis difficulty from censoring of observation. To address this difficulty, we have developed a Bayesian-based multivariate survival analysis method, which can successfully estimate the joint probability density of survival times. In this work, we extended this method for the analysis of precedence, dependency and causality among multiple events. We applied this method to the electronic health records of 2,111 patients in a children's hospital in the US and the proposed analysis successfully shows the relation between times to two types of hospital visits for different medical issues. The overall result implies the usefulness of the multivariate survival analysis method in large-scale big data in a variety of areas including marketing, human resources, and e-commerce. Lastly, we suggest our future research directions based multivariate survival analysis method.

Compatibility for the Typhoon Damages Predicted by Korea Risk Assessment Model Input Data (한국형 재해평가모형(RAM)의 초기입력자료 적합성 평가)

  • Park, Jong-Kil;Lee, Bo-Ram;Jung, Woo-Sik
    • Journal of Environmental Science International
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    • v.24 no.7
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    • pp.865-874
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    • 2015
  • This study was conducted to investigate the correlation between the distribution chart and input data of the predicted 3-second gust and damage cost, by using the forecast field and analysis field of Regional Data Assimilation Prediction System (RDAPS) as initial input data of Korea risk assessment model (RAM) developed in the preceding study. In this study the cases of typhoon Rusa which caused occurred great damage to the Korean peninsula was analyzed to assess the suitability of initial input data. As a result, this study has found out that the distribution chart from the forecast field and analysis field predicted from the point where the effect due to the typhoon began had similarity in both 3-second gust and damage cost with the course of time. As a result of examining the correlation, the 3-second gust had over 0.8, and it means that the forecast field and analysis field show similar results. This study has shown that utilizing the forecast field as initial input data of Korea RAM could suit the purpose of pre-disaster prevention.